Algorithms and Software Engineering for Professionals (Eduonix)

Algorithms and Software Engineering for Professionals (Eduonix)

Learn algorithms, data structures & the basics of data structure programs in this algorithms & software engineering course. Everything has a beginning and everything must be built from the ground up. This holds true even when it comes to software engineering and programming languages. Data structures provide a grounding for programming language and hold data and codes that determine what action will trigger what reaction.

Data structures and Algorithms are two important concepts when it comes to learning any programming language, functional or object oriented, from the ground up. In order to master a language, you must first master the basic groundwork for that language.

Data structures such as lists, trees, maps, etc. represent underlying data and are often required to be sorted and merged, transformed and matched in some way. To do this manually, it would require a lot of time and man power, which is where algorithms play a crucial role. Software engineers have created algorithms that provide a solution for this task, which is consistent, repeatable and testable with a set of metrics to quantify performance.
For your system to work without a hitch, your data structures must be perform perfectly, which means that your algorithms should be accurate and designed for efficiency. This course is where you can learn exactly how to do that!
We have designed a course to get you back to basics, so that you can create clean, efficient and powerful algorithms to help you improve the performance of your system and avoid any major critical bottleneck during operations.
This course has been broken down into nine sections that cover five major categories of algorithms as well as its underlying concepts: Cryptography, Compiler Theory, Signal Processing, Data Analysis, and Graph Databases.
In addition to theory, the course also includes numerous practical examples and applications of data structures and algorithms. Practical application is definitely important, especially when it comes to algorithms because in tech interviews and tests, questions are usually asked on the applicant’s ability to solve problems by creating algorithms that are based on the theory. So, this course will make a great refresher if you are trying to study for a test or apply for a job in the tech field!
At the end of this course, you will:

  • Have a deeper understanding of algorithms and its basic concepts
  • Understand acronyms such as ADT, AST, BFS and DFS
  • Have learned recursion and its relationship to concurrency (multi branch, memoization) and ADT’s like Trees and Graphs
  • Understand trees and the rotation operations used in balancing.
  • Know in detail about parsing grammars with Stacks and Queues and related tools like AST based parsers the beginning step on the road to Compiler theory
  • Understand operations with Primes and engaged some of the interesting and accessible underlying mathematics like Fermat's theorem

With the fast-paced development in the field of Software Engineering, it is impossible to predict future technologies and languages that may be written. Hence, it is important to understand the pure concepts that are the building blocks of each language and technology that may arise.
So, what are you waiting for? Let's master Software Engineering and become an Algorithm specialist with this course.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Algorithmic Thinking (Part 2) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 2) (Coursera)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Oct 5th 2026
4 Weeks
Build A Board Game Predictor Using Machine Learning (Eduonix) Eduonix
Eduonix Learning Solutions Pvt. Ltd.

Build A Board Game Predictor Using Machine Learning (Eduonix)

Learn linear regression algorithm building a real project. Machine Learning is slowly spreading its tentacles into all aspects of technology and even further. Better algorithms are helping devices become smarter and users to become more informed. Now, its time to add a little fun to Machine Learning and in this course, we have tried to do exactly that!

Self Paced
Self-Paced
Software Developer Career Guide and Interview Preparation (Coursera) Coursera
IBM

Software Developer Career Guide and Interview Preparation (Coursera)

This course is designed to prepare you to enter the job market as a software developer. It provides guidance about the regular functions and tasks of developers, as well as the opportunities of the profession and some options for career development. It explains practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch.

Oct 5th 2026
3 Weeks
Probabilistic Graphical Models 3: Learning (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 3: Learning (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Sep 28th 2026
5-12 Weeks
Ethical Issues in Data Science (Coursera) Coursera
University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.

Sep 28th 2026
5-12 Weeks
Analytic Combinatorics (Coursera) Coursera
Princeton University

Analytic Combinatorics (Coursera)

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations. All the features of this course are available for free. It does not offer a certificate upon completion.

Oct 5th 2026
5-12 Weeks
Information Theory (Coursera) Coursera
The Chinese University of Hong Kong

Information Theory (Coursera)

At the completion of this course, the student should be able to: demonstrate knowledge and understanding of the fundamentals of information theory; appreciate the notion of fundamental limits in communication systems and more generally all systems; develop deeper understanding of communication systems; apply the concepts of information theory to various disciplines in information science.

Oct 5th 2026
13-24 Weeks
Estruturas de dados Python (Coursera) Coursera
University of Michigan

Estruturas de dados Python (Coursera)

Este curso apresentará as estruturas de dados centrais da linguagem de programação Python. Vamos superar os fundamentos da programação de procedimentos e explorar como podemos usar as estruturas de dados integradas do Python, como listas, dicionários e tuplas, para realizar análises de dados cada vez mais complexas. Este curso cobrirá os capítulos 6 a 10 do livro “Python para Todos”. Este curso aborda o Python 3.

Oct 5th 2026
5-12 Weeks
Parallel programming (Scala 2 version) (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Parallel programming (Scala 2 version) (Coursera)

With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this course, you'll learn the fundamentals of parallel programming, from task parallelism to data parallelism. In particular, you'll see how many familiar ideas from functional programming map perfectly to to the data parallel paradigm. We'll start the nuts and bolts how to effectively parallelize familiar collections operations, and we'll build up to parallel collections, a production-ready data parallel collections library available in the Scala standard library.

Oct 5th 2026
4 Weeks
Code Yourself! An Introduction to Programming (Coursera) Coursera
University of Edinburgh,Universidad ORT Uruguay

Code Yourself! An Introduction to Programming (Coursera)

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer.

Sep 28th 2026
5-12 Weeks
Approximation Algorithms Part II (Coursera) Coursera
École normale supérieure

Approximation Algorithms Part II (Coursera)

This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques.

Sep 28th 2026
4 Weeks